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纤维球成像技术对脑白质微观结构的建模研究。

Modeling white matter microstructure with fiber ball imaging.

机构信息

Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.

Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.

出版信息

Neuroimage. 2018 Aug 1;176:11-21. doi: 10.1016/j.neuroimage.2018.04.025. Epub 2018 Apr 13.

DOI:10.1016/j.neuroimage.2018.04.025
PMID:29660512
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6064190/
Abstract

Fiber ball imaging (FBI) provides a means of calculating the fiber orientation density function (fODF) in white matter from diffusion MRI (dMRI) data obtained over a spherical shell with a b-value of about 4000 s/mm or higher. By supplementing this FBI-derived fODF with dMRI data acquired for two lower b-value shells, it is shown that several microstructural parameters may be estimated, including the axonal water fraction (AWF) and the intrinsic intra-axonal diffusivity. This fiber ball white matter (FBWM) modeling method is demonstrated for dMRI data acquired from healthy volunteers, and the results are compared with those of the white matter tract integrity (WMTI) method. Both the AWF and the intra-axonal diffusivity obtained with FBWM are found to be significantly larger than for WMTI, with the FBWM values for the intra-axonal diffusivity being more consistent with recent results obtained using isotropic diffusion weighting. An important practical advantage of FBWM is that the only nonlinear fitting required is the minimization of a cost function with just a single free parameter, which facilitates the implementation of efficient and robust numerical routines.

摘要

纤维球成像(FBI)提供了一种从扩散 MRI(dMRI)数据中计算白质纤维方向密度函数(fODF)的方法,这些数据是在 b 值约为 4000 s/mm 或更高的球形壳内获得的。通过补充 FBI 衍生的 fODF 与两个较低 b 值壳的 dMRI 数据,表明可以估计几个微观结构参数,包括轴突水分数(AWF)和固有轴内扩散系数。该纤维球白质(FBWM)建模方法是针对从健康志愿者获得的 dMRI 数据进行演示的,并将结果与白质束完整性(WMTI)方法进行比较。发现 FBWM 获得的 AWF 和轴内扩散系数均明显大于 WMTI,FBWM 的轴内扩散系数值与最近使用各向同性扩散加权获得的结果更为一致。FBWM 的一个重要实际优势是,唯一需要的非线性拟合是仅使用单个自由参数最小化成本函数,这有利于实现高效和稳健的数值例程。

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